Knowing Knowledge

At the end of the first section of the book he presents these knowledge/learning ‘principles of connectivism’:

• Learning and knowledge require diversity of opinions to present the wholeÖand to permit selection of best approach.     
• Learning is a network formation process of connecting specialized nodes or information sources.    
• Knowledge rests in networks.
• Knowledge may reside in non-human appliances, and learning is enabled/facilitated by technology.
• Capacity to know more is more critical than what is currently known.     
• Learning and knowing are constant, on going processes (not end states or products).     
• Ability to see connections and recognize patterns and make sense between fields, ideas, and concepts is the core skill for individuals today.
• Currency (accurate, up-to-date knowledge) is the intent of all connectivist learning activities.
• Decision-making is learning. Choosing what to learn and the meaning of incoming information is seen through the lens of a shifting reality. While there is a right answer now, it may be wrong tomorrow due to alterations in the information climate affecting the decision.

A healthy learning environment, he says, is open, self-managed, fostered, and conducive to knowledge flow. He implies, as I have argued, that ‘just in time’ learning is usually better than ‘just in case’ learning, and that collaboration, receptiveness, engagement, pattern-recognition, direct experience, and sense-making are essential or conducive to the learning process.

Siemens introduces the concept of ‘context games’ — interactions where our understandings and filters ‘compete’ in our (and other conversants’) contexts for our (and others’) acceptance.

This is all interesting, but after awhile you start to ask yourself how it can be useful. As fascinating as his theories and models are, I was hoping for something of practical value comparable to my contrasting of the old 1990s ‘acquire, store, add value, disseminate’ and the new 2000s ‘connect, canvass, synthesize, apply’ models of knowledge management:

In the second part of the book, Siemens describes how the principles he outlines in the first part might be applied. As I outlined in my earlier article, the approach he suggests to improve knowledge-sharing and learning in organizations is evolutionary and iterative rather than imposed. It responds to needs as they emerge rather than pre-supposing what those needs are. It demands a deep knowledge of the current state (which requires going out and talking to and observing people on the front lines to see what is really happening in their use of information and technology, and appreciating what they need and how they learn). It is a continuous process rather than a disjoint series of projects and ‘releases’. It is focused on developing competence and capacity, rather than just increasing the volume of information flows. For all of these reasons it is superior to the methodologies that have been Standard Operating Procedure in KM for more than a decade.

As the illustration at the top of this article shows, this approach is cyclical, two-way, and accommodates the needs of both managers and front-line staff. Change is perceived to be a consensual process: Only when there is a consensus that change is valuable will it “take root”. The four change enablers in the graphic operate almost like a pendulum: The demand for change (usually from customers, sometimes from management, sometimes from front-line workers’ learning and adaptation) precipitates ‘affordances’ (possibilities, ideas, alternatives and potentials) which, in turn, if they can achieve consensual traction, precipitate structural, systems, and infrastructure change within the organization, which, in turn, finally produce new methods and processes — different ways of doing things in the organization.

Or, in other words, needs -> possibilities -> change programs -> new processes & tools. Then, the adoption of these new processes & tools (often in unanticipated ways) yields new change programs and raises new possibilities that evoke new ëneedsí. Through several iterations (swings of the pendulum) all four elements converge on a new stasis, until new needs and change pressures restart the process.

A healthy knowledge ecology (knowledge-sharing environment), Siemens says, has the following attributes: flexibility, diversity of tools (for obtaining content, context and connection), consistency and sufficiency of time and attention, trust, simplicity, encouragement, connectedness, decentralization, and tolerance for experimentation and failure, with ëspaceí for experts and novices to meet, self-expression, debate, dialogue, search for archived knowledge, structured learning, communication of news, and nurturing of ideas. Networks form within such ecologies, and provide better knowledge and learning environments than hierarchies: As Siemens said (better, I think) in another article:

In the same article (and also in the book), Siemens eloquently describes the way in which knowledge/understanding emerges in social, ecological and other complex environments, much to the consternation of organizationsí command-and-control types:

Part of my responsibility in my current contract assignment is increasing the awareness and accessibility of the available tools, content and other resources among our employees and customers. Thereís a strong temptation to ëprescribeí how and when these resources should be used (as I did with my communication tool decision tree), but while these ëprescriptionsí may be useful guidance (especially for novice users) it is important that we allow and encourage employees and customers, individually and collectively, to use these resources as they see fit and share their ëadoptionsí with others, and understand and accommodate rather than proscribing their problem workarounds.

 
I would have liked to read more in Siemensí book about the cultural implications of decentralization and networking of knowledge. Some would have us believe that networks threaten the very existence of hierarchy, but Iím not so sure: In the organizations I know best, hierarchy continues to rule because management controls the purse-strings, and can ëstarveí those who fail to conform to its instructions. I used to believe that management also controlled decision-making, but Iíve come to believe that in most organizations decisions are de facto hugely decentralized: When the boss announces a decision that makes no sense to the front lines, the people on the front lines will figure out how to work around the decision in such a way they appear to be complying yet still manage to do things more sensibly. And if decisions donít produce action and behaviour change on the front lines, decision-making ëpowerí is impotent. But as the Max Planck quote below makes clear, one type of decision can help entrench hierarchy ñ the decision to fire those who are non-compliant and to promote those who comply, support and share the boss’ values.

Siemens calls for the redesign of organizations³ to enable decentralization and networked knowledge transfer, learning and action, but in large organizations this isnít going to happen ñ it will only occur, haphazardly, around the ëedgesí of organizations where those high in the hierarchy canít see it happening.

Although his prescription is, I think, impractical, his vision of an organization that enables effective knowledge-sharing, learning and collaboration is worth thinking about. Iím working on an article on ëworkaroundsí as the means by which most useful ‘unmechanizable’ work in organizations (i.e. thoughtful ëknowledge workí) actually gets done. Knowing Knowledge could be used as a ërecipe bookí of workarounds by savvy, practical knowledge workers.

If, as Siemens says, solutions are often contained within the problems themselves, then thatís a step in the right direction.

Notes:

1. Examples:

• “Whoever undertakes to set himself up as a judge of Truth and Knowledge is shipwrecked by the laughter of the gods.” (Albert Einstein)
• “An important scientific innovation rarely makes its way by by gradually winning over and converting its opponents. It rarely happens that Saul becomes Paul. What does happen is its opponents gradually die out and the growing generation is familiarized with the idea from the beginning.” (Max Planck)

2. He later seems to imply that “know who” is a special type of “know where”.

3. The redesign process has eight steps: Current state analysis, representation/evaluation, validation, learning/knowledge strategy (ëdevelopment mapí), ecology design/deployment, nurturing learning capacities/processes, assessment and revision.